2014
|
14. | Dirk Burkhardt; Kawa Nazemi; Jörn Kohlhammer Visual Process Support to Assist Users in Policy Making Book Chapter In: Peter Sonntagbauer; Kawa Nazemi; Susanne Sonntagbauer; Giorgio Prister; Dirk Burkhardt (Ed.): Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling, pp. 149–162, IGI Global, 2014, ISBN: 978-1-466-66236-0. @inbook{burkhardt2014visual,
title = {Visual Process Support to Assist Users in Policy Making},
author = {Dirk Burkhardt and Kawa Nazemi and Jörn Kohlhammer},
editor = {Peter Sonntagbauer and Kawa Nazemi and Susanne Sonntagbauer and Giorgio Prister and Dirk Burkhardt},
url = {https://www.igi-global.com/chapter/visual-process-support-to-assist-users-in-policy-making/116661, IGI Global},
doi = {10.4018/978-1-4666-6236-0.ch009},
isbn = {978-1-466-66236-0},
year = {2014},
date = {2014-06-01},
booktitle = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling},
journal = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling},
pages = {149--162},
publisher = {IGI Global},
series = {Handbook of Research},
crossref = {Sonntagbauer2014},
abstract = {The policy making process requires the involvement of various stakeholders, who bring in very heterogeneous experiences and skills concerning the policymaking domain, as well as experiences of ICT solutions. Current solutions are primarily designed to provide “one-solution-fits-all” answers, which in most cases fail the needs of all stakeholders. In this chapter, the authors introduce a new approach to assist users based on their tasks. Therefore, the system observes the interaction of the user and recognizes the current phase of the policymaking process and the profile of the user to assist him more sufficiently in solving his task. For this purpose, the system automatically enables or disables supporting features such as visualization, tools, and supporting techniques.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
The policy making process requires the involvement of various stakeholders, who bring in very heterogeneous experiences and skills concerning the policymaking domain, as well as experiences of ICT solutions. Current solutions are primarily designed to provide “one-solution-fits-all” answers, which in most cases fail the needs of all stakeholders. In this chapter, the authors introduce a new approach to assist users based on their tasks. Therefore, the system observes the interaction of the user and recognizes the current phase of the policymaking process and the profile of the user to assist him more sufficiently in solving his task. For this purpose, the system automatically enables or disables supporting features such as visualization, tools, and supporting techniques. |
13. | Kawa Nazemi; Martin Steiger; Dirk Burkhardt; Jörn Kohlhammer Information Visualization and Policy Modeling Book Chapter In: Peter Sonntagbauer; Kawa Nazemi; Susanne Sonntagbauer; Giorgio Prister; Dirk Burkhardt (Ed.): Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling, pp. 175–215, Business Science Reference (IGI Global), Hershey PA, USA, Hershey PA, USA, 2014, ISBN: 978-1-466-66236-0. @inbook{nazemi2014information,
title = {Information Visualization and Policy Modeling},
author = {Kawa Nazemi and Martin Steiger and Dirk Burkhardt and Jörn Kohlhammer},
editor = {Peter Sonntagbauer and Kawa Nazemi and Susanne Sonntagbauer and Giorgio Prister and Dirk Burkhardt},
url = {https://www.igi-global.com/chapter/information-visualization-and-policy-modeling/116664, IGI Global},
doi = {10.4018/978-1-4666-6236-0.ch011},
isbn = {978-1-466-66236-0},
year = {2014},
date = {2014-06-01},
booktitle = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling},
journal = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling},
pages = {175--215},
publisher = {Business Science Reference (IGI Global), Hershey PA, USA},
address = {Hershey PA, USA},
series = {Handbook of Research},
crossref = {Sonntagbauer2014},
abstract = {Policy design requires the investigation of various data in several design steps for making the right decisions, validating, or monitoring the political environment. The increasing amount of data is challenging for the stakeholders in this domain. One promising way to access the “big data” is by abstracted visual patterns and pictures, as proposed by information visualization. This chapter introduces the main idea of information visualization in policy modeling. First abstracted steps of policy design are introduced that enable the identification of information visualization in the entire policy life-cycle. Thereafter, the foundations of information visualization are introduced based on an established reference model. The authors aim to amplify the incorporation of information visualization in the entire policy design process. Therefore, the aspects of data and human interaction are introduced, too. The foundation leads to description of a conceptual design for social data visualization, and the aspect of semantics plays an important role.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Policy design requires the investigation of various data in several design steps for making the right decisions, validating, or monitoring the political environment. The increasing amount of data is challenging for the stakeholders in this domain. One promising way to access the “big data” is by abstracted visual patterns and pictures, as proposed by information visualization. This chapter introduces the main idea of information visualization in policy modeling. First abstracted steps of policy design are introduced that enable the identification of information visualization in the entire policy life-cycle. Thereafter, the foundations of information visualization are introduced based on an established reference model. The authors aim to amplify the incorporation of information visualization in the entire policy design process. Therefore, the aspects of data and human interaction are introduced, too. The foundation leads to description of a conceptual design for social data visualization, and the aspect of semantics plays an important role. |
12. | Kawa Nazemi; Dirk Burkhardt; Reimond Retz; Arjan Kuijper; Jörn Kohlhammer Adaptive Visualization of Linked-Data Proceedings Article In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Ryan McMahan; Jason Jerald; Hui Zhang; Steven M Drucker; Chandra Kambhamettu; Maha El Choubassi; Zhigang Deng; Mark Carlson (Ed.): Proceedings of International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing., pp. 872–883, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-14364-4. @inproceedings{Nazemi2014b,
title = {Adaptive Visualization of Linked-Data},
author = {Kawa Nazemi and Dirk Burkhardt and Reimond Retz and Arjan Kuijper and Jörn Kohlhammer},
editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson},
url = {https://link.springer.com/chapter/10.1007/978-3-319-14364-4_84, Springer link},
doi = {10.1007/978-3-319-14364-4_84},
isbn = {978-3-319-14364-4},
year = {2014},
date = {2014-03-01},
booktitle = {Proceedings of International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing.},
pages = {872--883},
publisher = {Springer International Publishing},
address = {Cham},
series = {LNCS 8888},
abstract = {Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictures and amplify cognition. Although the research on adaptive visualizations grew in the last years, the existing approaches do not consider the transformation pipeline from data to visual representation for a more efficient and effective adaptation. Further todays systems commonly require an initial training by experts from the field and are limited to adaptation based either on user behavior or on data characteristics. A combination of both is not proposed to our knowledge. This paper introduces an enhanced instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on content, visual layout, visual presentation, and visual interface. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonical requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictures and amplify cognition. Although the research on adaptive visualizations grew in the last years, the existing approaches do not consider the transformation pipeline from data to visual representation for a more efficient and effective adaptation. Further todays systems commonly require an initial training by experts from the field and are limited to adaptation based either on user behavior or on data characteristics. A combination of both is not proposed to our knowledge. This paper introduces an enhanced instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on content, visual layout, visual presentation, and visual interface. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonical requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling. |
11. | Kawa Nazemi; Dirk Burkhardt; Wilhelm Retz; Jörn Kohlhammer Adaptive Visualization of Social Media Data for Policy Modeling Proceedings Article In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Ryan McMahan; Jason Jerald; Hui Zhang; Steven M Drucker; Chandra Kambhamettu; Maha El Choubassi; Zhigang Deng; Mark Carlson (Ed.): Proceeding of the International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing., pp. 333–344, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-14249-4. @inproceedings{Nazemi2014,
title = {Adaptive Visualization of Social Media Data for Policy Modeling},
author = {Kawa Nazemi and Dirk Burkhardt and Wilhelm Retz and Jörn Kohlhammer},
editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson},
url = {https://link.springer.com/chapter/10.1007/978-3-319-14249-4_32, Springer link},
doi = {10.1007/978-3-319-14249-4_32},
isbn = {978-3-319-14249-4},
year = {2014},
date = {2014-01-01},
booktitle = {Proceeding of the International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing.},
pages = {333--344},
publisher = {Springer International Publishing},
address = {Cham},
series = {LNCS 8887},
abstract = {The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens' demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens' demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process. |
10. | Kawa Nazemi; Arjan Kuijper; Marco Hutter; Jörn Kohlhammer; Dieter W Fellner Measuring Context Relevance for Adaptive Semantics Visualizations Proceedings Article In: Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business, pp. 14:1–14:8, ACM, Graz, Austria, 2014, ISBN: 978-1-4503-2769-5, (Honourable Mention). @inproceedings{Nazemi:2014:MCR:2637748.2638416,
title = {Measuring Context Relevance for Adaptive Semantics Visualizations},
author = {Kawa Nazemi and Arjan Kuijper and Marco Hutter and Jörn Kohlhammer and Dieter W Fellner},
url = {https://doi.acm.org/10.1145/2637748.2638416, ACM DL},
doi = {10.1145/2637748.2638416},
isbn = {978-1-4503-2769-5},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business},
pages = {14:1--14:8},
publisher = {ACM},
address = {Graz, Austria},
series = {i-KNOW '14},
abstract = {Semantics visualizations enable the acquisition of information to amplify the acquisition of knowledge. The dramatic increase of semantics in form of Linked Data and Linked-Open Data yield search databases that allow to visualize the entire context of search results. The visualization of this semantic context enables one to gather more information at once, but the complex structures may as well confuse and frustrate users. To overcome the problems, adaptive visualizations already provide some useful methods to adapt the visualization on users' demands and skills. Although these methods are very promising, these systems do not investigate the relevance of semantic neighboring entities that commonly build most information value. We introduce two new measurements for the relevance of neighboring entities: The Inverse Instance Frequency allows weighting the relevance of semantic concepts based on the number of their instances. The Direct Relation Frequency inverse Relations Frequency measures the relevance of neighboring instances by the type of semantic relations. Both measurements provide a weighting of neighboring entities of a selected semantic instance, and enable an adaptation of retinal variables for the visualized graph. The algorithms can easily be integrated into adaptive visualizations and enhance them with the relevance measurement of neighboring semantic entities. We give a detailed description of the algorithms to enable a replication for the adaptive and semantics visualization community. With our method, one can now easily derive the relevance of neighboring semantic entities of selected instances, and thus gain more information at once, without confusing and frustrating users.},
note = {Honourable Mention},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Semantics visualizations enable the acquisition of information to amplify the acquisition of knowledge. The dramatic increase of semantics in form of Linked Data and Linked-Open Data yield search databases that allow to visualize the entire context of search results. The visualization of this semantic context enables one to gather more information at once, but the complex structures may as well confuse and frustrate users. To overcome the problems, adaptive visualizations already provide some useful methods to adapt the visualization on users' demands and skills. Although these methods are very promising, these systems do not investigate the relevance of semantic neighboring entities that commonly build most information value. We introduce two new measurements for the relevance of neighboring entities: The Inverse Instance Frequency allows weighting the relevance of semantic concepts based on the number of their instances. The Direct Relation Frequency inverse Relations Frequency measures the relevance of neighboring instances by the type of semantic relations. Both measurements provide a weighting of neighboring entities of a selected semantic instance, and enable an adaptation of retinal variables for the visualized graph. The algorithms can easily be integrated into adaptive visualizations and enhance them with the relevance measurement of neighboring semantic entities. We give a detailed description of the algorithms to enable a replication for the adaptive and semantics visualization community. With our method, one can now easily derive the relevance of neighboring semantic entities of selected instances, and thus gain more information at once, without confusing and frustrating users. |
9. | Dirk Burkhardt; Kawa Nazemi; Jose Daniel Encarnacao; Wilhelm Retz; Jörn Kohlhammer Visualization Adaptation Based on Environmental Influencing Factors Proceedings Article In: Masaaki Kurosu (Ed.): International Conference on Human-Computer (HCI 2014). Human-Computer Interaction. Theories, Methods, and Tools., pp. 411–422, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-07233-3. @inproceedings{Burkhardt2014f,
title = {Visualization Adaptation Based on Environmental Influencing Factors},
author = {Dirk Burkhardt and Kawa Nazemi and Jose Daniel Encarnacao and Wilhelm Retz and Jörn Kohlhammer},
editor = {Masaaki Kurosu},
url = {https://link.springer.com/chapter/10.1007/978-3-319-07233-3_38, Springer link},
isbn = {978-3-319-07233-3},
year = {2014},
date = {2014-01-01},
booktitle = {International Conference on Human-Computer (HCI 2014). Human-Computer Interaction. Theories, Methods, and Tools.},
pages = {411--422},
publisher = {Springer International Publishing},
address = {Cham},
series = {LNCS 8510},
abstract = {Working effectively with computer-based devices is challenging, especially under mobile conditions, due to the various environmental influences. In this paper a visualization adaptation approach is described, to support the user under discriminatory environmental conditions. For this purpose, a context model for environmental influencing factors is being defined. Based on this context model, an approach to adapt visualizations in regards of certain environmental influences is being evolved, such as the light intensity, air quality, or heavy vibrations.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Working effectively with computer-based devices is challenging, especially under mobile conditions, due to the various environmental influences. In this paper a visualization adaptation approach is described, to support the user under discriminatory environmental conditions. For this purpose, a context model for environmental influencing factors is being defined. Based on this context model, an approach to adapt visualizations in regards of certain environmental influences is being evolved, such as the light intensity, air quality, or heavy vibrations. |
2013
|
8. | Christian Stab; Dirk Burkhardt; Matthias Breyer; Kawa Nazemi Visualizing Search Results of Linked Open Data Book Chapter In: Tim Hussein; Heiko Paulheim; Stephan Lukosch; Jürgen Ziegler; Ga"elle Calvary (Ed.): Semantic Models for Adaptive Interactive Systems, pp. 133–149, Springer London, London, 2013, ISBN: 978-1-4471-5301-6. @inbook{Stab2013,
title = {Visualizing Search Results of Linked Open Data},
author = {Christian Stab and Dirk Burkhardt and Matthias Breyer and Kawa Nazemi},
editor = {Tim Hussein and Heiko Paulheim and Stephan Lukosch and Jürgen Ziegler and Ga"elle Calvary},
url = {https://link.springer.com/chapter/10.1007/978-1-4471-5301-6_7, Springer link},
doi = {10.1007/978-1-4471-5301-6_7},
isbn = {978-1-4471-5301-6},
year = {2013},
date = {2013-10-01},
booktitle = {Semantic Models for Adaptive Interactive Systems},
pages = {133--149},
publisher = {Springer London},
address = {London},
series = {Human–Computer Interaction Series},
abstract = {Finding accurate information of high quality is still a challenging task particularly with regards to the increasing amount of resources in current information systems. This is especially true if policy decisions that impact humans, economy or environment are based on the demanded information. For improving search result generation and analyzing user queries more and more information retrieval systems utilize Linked Open Data and other semantic knowledge bases. Nevertheless, the semantic information that is used during search result generation mostly remains hidden from the users although it significantly supports users in understanding and assessing search results. The presented approach combines information visualizations with semantic information for offering visual feedback about the reasons the results were retrieved. It visually represents the semantic interpretation and the relation between query terms and search results to offer more transparency in search result generation and allows users to unambiguously assess the relevance of the retrieved resources for their individual search. The approach also supports the common search strategies by providing visual feedback for query refinement and enhancement. Besides the detailed description of the search system, an evaluation of the approach shows that the use of semantic information considerably supports users in assessment and decision-making tasks.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Finding accurate information of high quality is still a challenging task particularly with regards to the increasing amount of resources in current information systems. This is especially true if policy decisions that impact humans, economy or environment are based on the demanded information. For improving search result generation and analyzing user queries more and more information retrieval systems utilize Linked Open Data and other semantic knowledge bases. Nevertheless, the semantic information that is used during search result generation mostly remains hidden from the users although it significantly supports users in understanding and assessing search results. The presented approach combines information visualizations with semantic information for offering visual feedback about the reasons the results were retrieved. It visually represents the semantic interpretation and the relation between query terms and search results to offer more transparency in search result generation and allows users to unambiguously assess the relevance of the retrieved resources for their individual search. The approach also supports the common search strategies by providing visual feedback for query refinement and enhancement. Besides the detailed description of the search system, an evaluation of the approach shows that the use of semantic information considerably supports users in assessment and decision-making tasks. |
7. | Kawa Nazemi; Reimond Retz; Jürgen Bernard; Jörn Kohlhammer; Dieter Fellner Adaptive Semantic Visualization for Bibliographic Entries Proceedings Article In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Baoxin Li; Fatih Porikli; Victor Zordan; James Klosowski; Sabine Coquillart; Xun Luo; Min Chen; David Gotz (Ed.): Proceedings of International Symposium on Visual Computing (ISVC 2013). Advances in Visual Computing., pp. 13–24, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, ISBN: 978-3-642-41939-3. @inproceedings{Nazemi2013,
title = {Adaptive Semantic Visualization for Bibliographic Entries},
author = {Kawa Nazemi and Reimond Retz and Jürgen Bernard and Jörn Kohlhammer and Dieter Fellner},
editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Baoxin Li and Fatih Porikli and Victor Zordan and James Klosowski and Sabine Coquillart and Xun Luo and Min Chen and David Gotz},
url = {https://link.springer.com/chapter/10.1007/978-3-642-41939-3_2, Springer link},
doi = {10.1007/978-3-642-41939-3_2},
isbn = {978-3-642-41939-3},
year = {2013},
date = {2013-01-01},
booktitle = {Proceedings of International Symposium on Visual Computing (ISVC 2013). Advances in Visual Computing.},
pages = {13--24},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
series = {LNCS 8034},
abstract = {Adaptive visualizations aim to reduce the complexity of visual representations and convey information using interactive visualizations. Although the research on adaptive visualizations grew in the last years, the existing approaches do not make use of the variety of adaptable visual variables. Further the existing approaches often premises experts, who has to model the initial visualization design. In addition, current approaches either incorporate user behavior or data types. A combination of both is not proposed to our knowledge. This paper introduces the instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on visual layout and visual presentation in a multiple visualization environment. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonic requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Adaptive visualizations aim to reduce the complexity of visual representations and convey information using interactive visualizations. Although the research on adaptive visualizations grew in the last years, the existing approaches do not make use of the variety of adaptable visual variables. Further the existing approaches often premises experts, who has to model the initial visualization design. In addition, current approaches either incorporate user behavior or data types. A combination of both is not proposed to our knowledge. This paper introduces the instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on visual layout and visual presentation in a multiple visualization environment. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonic requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling. |
2012
|
6. | Jörn Kohlhammer; Kawa Nazemi; Tobias Ruppert; Dirk Burkhardt Toward Visualization in Policy Modeling Journal Article In: IEEE Computer Graphics and Applications (CG&A), vol. 32, no. 5, pp. 84-89, 2012, ISSN: 0272-1716. @article{6311373,
title = {Toward Visualization in Policy Modeling},
author = {Jörn Kohlhammer and Kawa Nazemi and Tobias Ruppert and Dirk Burkhardt},
url = {https://ieeexplore.ieee.org/document/6311373/, IEEE Xplore},
doi = {10.1109/MCG.2012.107},
issn = {0272-1716},
year = {2012},
date = {2012-09-01},
journal = {IEEE Computer Graphics and Applications (CG&A)},
volume = {32},
number = {5},
pages = {84-89},
publisher = {IEEE Press},
abstract = {This article looks at the current and future roles of information visualization, semantics visualization, and visual analytics in policy modeling. Many experts believe that you can't overestimate visualization's role in this respect.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This article looks at the current and future roles of information visualization, semantics visualization, and visual analytics in policy modeling. Many experts believe that you can't overestimate visualization's role in this respect. |
5. | Dirk Burkhardt; Christian Stab; Martin Steiger; Matthias Breyer; Kawa Nazemi Interactive Exploration System: A User-Centered Interaction Approach in Semantics Visualizations Proceedings Article In: 2012 International Conference on Cyberworlds, pp. 261-267, IEEE, 2012, ISBN: 978-1-4673-2736-7. @inproceedings{6337431,
title = {Interactive Exploration System: A User-Centered Interaction Approach in Semantics Visualizations},
author = {Dirk Burkhardt and Christian Stab and Martin Steiger and Matthias Breyer and Kawa Nazemi},
doi = {10.1109/CW.2012.45},
isbn = {978-1-4673-2736-7},
year = {2012},
date = {2012-09-01},
booktitle = {2012 International Conference on Cyberworlds},
pages = {261-267},
publisher = {IEEE},
abstract = {Nowadays a wide range of input devices are available to users of technical systems. Especially modern alternative interaction devices, which are known from game consoles etc., provide a more natural way of interaction. In parallel to that the research on visualization of large amount of data advances very quickly. This research was also influenced by the semantic web and the idea of storing data in a structured and linked form. The semantically annotated data gains more and more importance in information acquisition processes. Especially the Linked Open Data (LOD) format already experienced a huge growth. However, the user-interfaces of web-applications mostly do not reflect the added value of semantics data. This paper describes the conceptual design and implementation of an Interactive Exploration System that offers a user-centered graphical environment of web-based knowledge repositories, to support and optimize explorative learning, and the integration of a taxonomy-based approach to enable the use of more natural interaction metaphors, as they are possible with modern devices like Wii Mote or Microsoft Kinect. Therefore we introduce a different classification for interaction devices, and current approaches for supporting the added values in semantics visualizations. Furthermore, we describe the concept of our IES, including a strategy to organize and structure today's existing input devices, and a semantics exploration system driven by user-experience. We conclude the paper with a description of the implementation of the IES and an application scenario.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Nowadays a wide range of input devices are available to users of technical systems. Especially modern alternative interaction devices, which are known from game consoles etc., provide a more natural way of interaction. In parallel to that the research on visualization of large amount of data advances very quickly. This research was also influenced by the semantic web and the idea of storing data in a structured and linked form. The semantically annotated data gains more and more importance in information acquisition processes. Especially the Linked Open Data (LOD) format already experienced a huge growth. However, the user-interfaces of web-applications mostly do not reflect the added value of semantics data. This paper describes the conceptual design and implementation of an Interactive Exploration System that offers a user-centered graphical environment of web-based knowledge repositories, to support and optimize explorative learning, and the integration of a taxonomy-based approach to enable the use of more natural interaction metaphors, as they are possible with modern devices like Wii Mote or Microsoft Kinect. Therefore we introduce a different classification for interaction devices, and current approaches for supporting the added values in semantics visualizations. Furthermore, we describe the concept of our IES, including a strategy to organize and structure today's existing input devices, and a semantics exploration system driven by user-experience. We conclude the paper with a description of the implementation of the IES and an application scenario. |
4. | Christian Stab; Matthias Breyer; Dirk Burkhardt; Kawa Nazemi; Jörn Kohlhammer Analytical semantics visualization for discovering latent signals in large text collections Proceedings Article In: Andreas Kerren; Stefan Seipel (Ed.): Proceedings of SIGRAD 2012; Interactive Visual Analysis of Data; November 29-30; 2012; Växjö; Sweden, pp. 83–86, Linköping University Linköping University Electronic Press, 2012, ISBN: 978-91-7519-723-4. @inproceedings{stab2012analytical,
title = {Analytical semantics visualization for discovering latent signals in large text collections},
author = {Christian Stab and Matthias Breyer and Dirk Burkhardt and Kawa Nazemi and Jörn Kohlhammer},
editor = {Andreas Kerren and Stefan Seipel},
url = {https://www.ep.liu.se/ecp/081/011/ecp12081011.pdf, full text},
isbn = {978-91-7519-723-4},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of SIGRAD 2012; Interactive Visual Analysis of Data; November 29-30; 2012; Växjö; Sweden},
number = {081},
pages = {83--86},
publisher = {Linköping University Electronic Press},
organization = {Linköping University},
abstract = {Considering the increasing pressure of competition and high dynamics of markets; the early identification and specific handling of novel developments and trends becomes more and more important for competitive companies. Today; those signals are encoded in large amounts of textual data like competitors’ web sites; news articles; scientific publications or blog entries which are freely available in the web. Processing large amounts of textual data is still a tremendous challenge for current business analysts and strategic decision makers. Although current information systems are able to process that amount of data and provide a wide range of information retrieval tools; it is almost impossible to keep track of each thread or opportunity. The presented approach combines semantic search and data mining techniques with interactive visualizations for analyzing and identifying weak signals in large text collections. Beside visual summarization tools; it includes an enhanced trend visualization that supports analysts in identifying latent topic-related relations between competitors and their temporal relevance. It includes a graph-based visualization tool for representing relations identified during semantic analysis. The interaction design allows analysts to verify their retrieved hypothesis by exploring the documents that are responsible for the current view.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Considering the increasing pressure of competition and high dynamics of markets; the early identification and specific handling of novel developments and trends becomes more and more important for competitive companies. Today; those signals are encoded in large amounts of textual data like competitors’ web sites; news articles; scientific publications or blog entries which are freely available in the web. Processing large amounts of textual data is still a tremendous challenge for current business analysts and strategic decision makers. Although current information systems are able to process that amount of data and provide a wide range of information retrieval tools; it is almost impossible to keep track of each thread or opportunity. The presented approach combines semantic search and data mining techniques with interactive visualizations for analyzing and identifying weak signals in large text collections. Beside visual summarization tools; it includes an enhanced trend visualization that supports analysts in identifying latent topic-related relations between competitors and their temporal relevance. It includes a graph-based visualization tool for representing relations identified during semantic analysis. The interaction design allows analysts to verify their retrieved hypothesis by exploring the documents that are responsible for the current view. |
2011
|
3. | Dirk Burkhardt; Kawa Nazemi; Matthias Breyer; Christian Stab; Arjan Kuijper SemaZoom: Semantics Exploration by Using a Layer-Based Focus and Context Metaphor Proceedings Article In: Masaaki Kurosu (Ed.): Human Centered Design, pp. 491–499, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21753-1. @inproceedings{10.1007/978-3-642-21753-1_55,
title = {SemaZoom: Semantics Exploration by Using a Layer-Based Focus and Context Metaphor},
author = {Dirk Burkhardt and Kawa Nazemi and Matthias Breyer and Christian Stab and Arjan Kuijper},
editor = {Masaaki Kurosu},
url = {https://doi.org/10.1007/978-3-642-21753-1_55, DOI
https://link.springer.com/chapter/10.1007/978-3-642-21753-1_55, Springer page},
doi = {10.1007/978-3-642-21753-1_55},
isbn = {978-3-642-21753-1},
year = {2011},
date = {2011-01-01},
booktitle = {Human Centered Design},
pages = {491--499},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
series = {LNCS 6776},
abstract = {The Semantic Web is a powerful technology for organizing the data in our information based society. The collection and organization of information is an important step for showing important information to interested people. But the usage of such semantic-based data sources depends on effective and efficient information visualizations. Currently different kinds of visualizations in general and visualization metaphors do exist. Many of them are also applied for semantic data source, but often they are designed for semantic web experts and neglecting the normal user and his perception of an easy useable visualization. This kind of user needs less information, but rather a reduced qualitative view on the data. These two aspects of large amount of existing data and one for normal users easy to understand visualization is often not reconcilable. In this paper we create a concept for a visualization to show a bigger set of information to such normal users without overstraining them, because of layer-based data visualization, next to an integration of a Focus and Context metaphor.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Semantic Web is a powerful technology for organizing the data in our information based society. The collection and organization of information is an important step for showing important information to interested people. But the usage of such semantic-based data sources depends on effective and efficient information visualizations. Currently different kinds of visualizations in general and visualization metaphors do exist. Many of them are also applied for semantic data source, but often they are designed for semantic web experts and neglecting the normal user and his perception of an easy useable visualization. This kind of user needs less information, but rather a reduced qualitative view on the data. These two aspects of large amount of existing data and one for normal users easy to understand visualization is often not reconcilable. In this paper we create a concept for a visualization to show a bigger set of information to such normal users without overstraining them, because of layer-based data visualization, next to an integration of a Focus and Context metaphor. |
2010
|
2. | Kawa Nazemi; Matthias Breyer; Dirk Burkhardt; Dieter W Fellner Visualization Cockpit: Orchestration of Multiple Visualizations for Knowledge-Exploration Journal Article In: International Journal of Advanced Corporate Learning, vol. 3, no. 4, pp. 26-34, 2010, ISSN: 1867-5565. @article{C35-P-21710,
title = {Visualization Cockpit: Orchestration of Multiple Visualizations for Knowledge-Exploration},
author = {Kawa Nazemi and Matthias Breyer and Dirk Burkhardt and Dieter W Fellner},
url = {https://online-journals.org/index.php/i-jac/article/view/1473, iJAC Journal
https://online-journals.org/index.php/i-jac/article/download/1473/1560.pdf, Full Paper},
issn = {1867-5565},
year = {2010},
date = {2010-01-01},
journal = {International Journal of Advanced Corporate Learning},
volume = {3},
number = {4},
pages = {26-34},
abstract = {Semantic-Web technologies and ontology-based information processing systems are established techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies, so they work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The customization of the presentation itself and the interaction techniques with these presentation artifacts is a key question for gainful and effective work with semantic information. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Semantic-Web technologies and ontology-based information processing systems are established techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies, so they work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The customization of the presentation itself and the interaction techniques with these presentation artifacts is a key question for gainful and effective work with semantic information. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps. |
1. | Christian Stab; Kawa Nazemi; Dieter W Fellner SemaTime - Timeline Visualization of Time-Dependent Relations and Semantics Conference Advances in Visual Computing. 6th International Symposium, Proceeding of ISVC 2010, LNCS 6455 Springer-Verlag, Berlin Heidelberg, 2010, ISBN: 978-3-642-17276-2. @conference{C35-P-21759,
title = {SemaTime - Timeline Visualization of Time-Dependent Relations and Semantics},
author = {Christian Stab and Kawa Nazemi and Dieter W Fellner},
editor = {[G. Bebis ]},
url = {https://doi.org/10.1007/978-3-642-17277-9_53, DOI
https://link.springer.com/chapter/10.1007/978-3-642-17277-9_53, Springer Link},
doi = {10.1007/978-3-642-17277-9_53},
isbn = {978-3-642-17276-2},
year = {2010},
date = {2010-01-01},
booktitle = {Advances in Visual Computing. 6th International Symposium, Proceeding of ISVC 2010},
pages = {514-523},
publisher = {Springer-Verlag},
address = {Berlin Heidelberg},
series = {LNCS 6455},
abstract = {Timeline based visualizations arrange time-dependent entities along a time-axis and are used in many different domains like digital libraries, criminal investigation and medical information systems to support users in understanding chronological structures. By the use of semantic technologies, the information is categorized in a domain-specific, hierarchical schema and specified by semantic relations. Commonly semantic relations in timeline visualizations are depicted by interconnecting entities with a directed edge. However it is possible that semantic relations change in the course of time. In this paper we introduce a new timeline visualization for time-dependent semantics called SemaTime that offers a hierarchical categorization of time-dependent entities including navigation and filtering features. We also present a novel concept for visualizing time-dependent relations that allows the illustration of time-varying semantic relations and affords an easy understandable
visualization of complex, time-dependent interrelations.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Timeline based visualizations arrange time-dependent entities along a time-axis and are used in many different domains like digital libraries, criminal investigation and medical information systems to support users in understanding chronological structures. By the use of semantic technologies, the information is categorized in a domain-specific, hierarchical schema and specified by semantic relations. Commonly semantic relations in timeline visualizations are depicted by interconnecting entities with a directed edge. However it is possible that semantic relations change in the course of time. In this paper we introduce a new timeline visualization for time-dependent semantics called SemaTime that offers a hierarchical categorization of time-dependent entities including navigation and filtering features. We also present a novel concept for visualizing time-dependent relations that allows the illustration of time-varying semantic relations and affords an easy understandable
visualization of complex, time-dependent interrelations. |